Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for calibrating a touchscreen panel, where the touchscreen panel is arranged in a working range of an industrial robot so that the industrial robot is able to touch a touchscreen of the touchscreen panel, the method including the steps of: (a) defining at least one area of the touchscreen with predetermined accuracy for position measuring; (b) recording a plurality of kinematic parameters of the industrial robot on a plurality of first touch points on the at least one area of the touchscreen; (c) recording a plurality of first position values on the plurality of first touch points on the at least one area of the touchscreen; (d) determining a first calibration data for the kinematic model of the industrial robot using the kinematic parameters and using the first position values; (e) computationally correcting errors of the kinematic model of the industrial robot using the first calibration data; (f) recording a plurality of second position values on a plurality of second touch points on the at least one area with at least a portion of its border extending outwards; (g) determining a second calibration data for the touchscreen using the kinematic parameters and using the second position values; (h) computationally correcting errors of position measurement of the touchscreen using the second calibration data; and iteratively repeating the steps (b) through (h) for different postures of the industrial robot until the iteration step no longer results in significant improvement of the error correction of the kinematic model of the industrial robot.
This technical summary describes a method for calibrating a touchscreen panel used in conjunction with an industrial robot. The method addresses the challenge of ensuring precise interaction between the robot and the touchscreen, which is placed within the robot's working range. The process involves defining specific areas on the touchscreen with predetermined accuracy for position measurement. The industrial robot touches multiple points within these areas, and both the robot's kinematic parameters (e.g., joint angles, positions) and the corresponding touchscreen position values are recorded. Using this data, a first calibration dataset is generated to correct errors in the robot's kinematic model. The robot's kinematic model is then refined iteratively. Next, additional touch points are recorded, including points near the edges of the defined areas, to generate a second calibration dataset for the touchscreen itself. This dataset corrects positional measurement errors on the touchscreen. The entire process is repeated with different robot postures until further iterations no longer significantly improve the calibration accuracy. The method ensures that both the robot's movement and the touchscreen's position detection are accurately aligned, enhancing the precision of touch-based interactions in industrial automation.
2. The method according to claim 1 , wherein: a number of the first touch points is equal to or above a number of the kinematics parameter of the industrial robot.
This invention relates to industrial robot control systems, specifically improving motion planning and execution by optimizing touch point selection. The problem addressed is ensuring precise and efficient robot movement by dynamically adjusting the number of touch points used in trajectory planning based on the robot's kinematic parameters. The system determines a set of first touch points for a robot's end effector to follow during movement, where the number of these touch points is equal to or greater than the number of kinematic parameters of the industrial robot. This ensures sufficient control points to accurately define the robot's motion while avoiding excessive computational overhead. The kinematic parameters define the robot's degrees of freedom, such as joint angles or Cartesian coordinates, and the touch points serve as waypoints that guide the robot's path. By matching or exceeding the number of kinematic parameters with touch points, the system ensures that the robot's motion is fully constrained and controllable, reducing errors and improving precision. This approach is particularly useful in applications requiring high accuracy, such as assembly, welding, or material handling, where precise movement is critical. The method dynamically adjusts the touch point count based on the robot's configuration, optimizing both performance and computational efficiency.
3. The method according to claim 2 , wherein: a number of the second touch points is equal to or above a dimensional number of the touchscreen.
A method for touchscreen input processing addresses the challenge of accurately detecting and interpreting multi-touch gestures on a touchscreen device. The method involves analyzing touch points detected on the touchscreen to distinguish between intentional user inputs and unintentional or erroneous touches. Specifically, the method evaluates the number of touch points to determine if they meet or exceed the dimensional number of the touchscreen, which refers to the minimum number of touch points required to perform a valid multi-touch gesture. For example, a touchscreen with a dimensional number of two would require at least two touch points to register a valid gesture, such as a pinch or zoom. The method ensures that only meaningful gestures are processed, reducing false positives from accidental or spurious touches. This improves the reliability and responsiveness of touchscreen interfaces, particularly in applications where precise gesture recognition is critical, such as graphic design, gaming, or virtual reality. The method may be implemented in software or firmware within the touchscreen device, allowing for real-time processing of touch inputs. By dynamically adjusting the threshold based on the touchscreen's capabilities, the method adapts to different device configurations and user interactions, enhancing overall usability.
4. The method according to claim 3 , wherein in the step (e), the at least area is extended to enclose the previous one.
This invention relates to a method for extending a defined area in a system, likely for purposes such as boundary adjustment, spatial analysis, or object tracking. The method addresses the problem of dynamically adjusting an area to include previously defined regions, ensuring continuity or expansion of coverage without gaps. The method involves multiple steps, including defining an initial area, processing data to identify relevant regions, and iteratively extending the area to encompass additional regions. Specifically, in the key step, the method extends the current area to fully enclose a previously defined area, ensuring that the new boundary incorporates all prior regions. This step is critical for maintaining spatial coherence, such as in mapping, surveillance, or environmental monitoring applications. The method may involve iterative refinement, where each extension step builds upon the previous area, ensuring that the final boundary is comprehensive. This approach is useful in scenarios where incremental updates are necessary, such as in real-time tracking or adaptive boundary adjustments. The invention likely improves accuracy and efficiency in systems requiring dynamic area management.
5. The method according to claim 3 , wherein: in the step (e), at least a portion of the second touch points are distributed in the extended part of the at least one area.
The invention relates to touch-sensitive input systems, particularly for devices with extended touch-sensitive areas. The problem addressed is improving touch input accuracy and usability in devices where touch-sensitive regions extend beyond a primary display or input area, such as foldable or multi-display devices. Traditional systems struggle to accurately detect and process touch inputs in these extended regions, leading to misinterpretation or ignored inputs. The method involves detecting touch points on a touch-sensitive surface, where the surface includes at least one primary area and an extended area adjacent to it. The method first identifies a first set of touch points in the primary area and a second set of touch points in the extended area. The system then processes these touch points to determine their spatial relationships and interactions. A key aspect is that at least some of the second touch points in the extended area are distributed in a way that maintains continuity with the primary area, ensuring seamless input detection across the entire touch-sensitive surface. This distribution helps the system accurately interpret multi-touch gestures, such as swipes or pinches, that span both the primary and extended areas. The method may also include filtering or prioritizing touch points based on their location or movement patterns to enhance input accuracy. The solution improves usability in devices with non-contiguous or irregularly shaped touch-sensitive surfaces by ensuring consistent and reliable touch detection across all regions.
6. The method according to claim 2 , wherein: in the step (e), the at least area is extended to enclose the previous one.
This invention relates to a method for processing image data, specifically for extending a selected area within an image to include a previously identified area. The method addresses the challenge of accurately and efficiently expanding image regions to encompass adjacent or overlapping areas, which is useful in applications such as object segmentation, image editing, and automated analysis. The method involves a multi-step process where an initial area within an image is identified and selected. This area is then extended to enclose a previously defined area, ensuring continuity and completeness in the selection. The extension process may involve analyzing spatial relationships, boundary conditions, or other image features to determine the optimal expansion. The method ensures that the extended area fully contains the previous area, preventing gaps or overlaps that could affect downstream processing. This approach is particularly valuable in scenarios where precise region selection is critical, such as medical imaging, autonomous vehicle perception, or computer vision tasks. By dynamically adjusting the selected area to include prior regions, the method improves accuracy and reduces manual intervention. The technique may also incorporate machine learning or heuristic-based algorithms to refine the extension process, adapting to different image types and complexities. The result is a seamless integration of multiple image regions, enhancing the reliability of subsequent analysis or editing operations.
7. The method according to claim 2 , wherein: in the step (e), at least a portion of the second touch points are distributed in the extended part of the at least one area.
A method for touch input processing in electronic devices addresses the challenge of accurately detecting and interpreting touch inputs, particularly in extended or non-standard touch-sensitive areas. The method involves capturing touch data from a touch-sensitive surface, identifying a first set of touch points corresponding to an initial touch event, and determining a first area encompassing these touch points. The method then predicts a second set of touch points based on the first area and a predefined rule, such as a geometric or probabilistic model. These predicted touch points are used to define an extended part of the first area, which may include regions beyond the initial touch points. The method then processes subsequent touch inputs by distributing at least a portion of the second touch points within this extended area, improving touch detection accuracy and responsiveness in dynamic or irregular touch surfaces. This approach is particularly useful in devices with curved, flexible, or multi-touch surfaces where traditional touch detection methods may fail to capture all relevant touch interactions. The method enhances touch input reliability by dynamically adjusting the detection area based on predicted touch behavior, reducing false positives and improving user experience.
8. The method according to claim 2 , further includes steps following the termination of the iteration: determining a third calibration data for the touchscreen using the kinematic parameters and using the second position values; and computationally correcting errors of position measurement of the touchscreen for the rest areas using the third calibration data.
This invention relates to touchscreen calibration, specifically improving accuracy in areas not directly touched during calibration. The problem addressed is that conventional touchscreen calibration methods may leave residual errors in regions between calibration points, leading to inaccurate touch position measurements. The solution involves a multi-step process that includes an initial calibration phase followed by an iterative refinement process. During the iterative process, a set of kinematic parameters is derived from touch position measurements, and these parameters are used to model the touchscreen's behavior. After the iteration terminates, a third calibration dataset is generated using the kinematic parameters and previously obtained position values. This third dataset is then applied to computationally correct position measurement errors in the remaining areas of the touchscreen, ensuring uniform accuracy across the entire surface. The method leverages the kinematic model to predict and compensate for distortions or inaccuracies in untouched regions, enhancing overall touchscreen performance. The approach is particularly useful in applications requiring high precision, such as industrial control systems or medical devices, where touch input reliability is critical.
9. The method according to claim 1 , wherein: a number of the second touch points is equal to or above a dimensional number of the touchscreen.
A method for touchscreen input processing addresses the challenge of accurately detecting and interpreting multi-touch gestures on a touchscreen device. The method involves detecting a plurality of touch points on the touchscreen, where each touch point corresponds to a user's contact with the screen. The method distinguishes between primary touch points, which are used for standard input, and secondary touch points, which may be used for additional or specialized input functions. The method further includes determining a dimensional number of the touchscreen, which refers to the number of independent touch points the touchscreen can simultaneously detect and process. The method ensures that the number of secondary touch points is equal to or exceeds this dimensional number, allowing for robust multi-touch gesture recognition. This approach enhances the accuracy and reliability of touchscreen input, particularly in applications requiring complex or simultaneous multi-touch interactions, such as gaming, drawing, or multi-user collaboration. The method may be implemented in touchscreen devices, including smartphones, tablets, and interactive displays, to improve user experience and input responsiveness.
10. The method according to claim 9 , wherein: in the step (e), the at least area is extended to enclose the previous one.
A method for processing image data involves analyzing a sequence of images to detect and track objects. The method addresses the challenge of accurately identifying and maintaining the boundaries of objects in dynamic scenes where their positions and shapes may change over time. The process includes capturing a series of images, identifying an object in a current image, and determining an area of interest around the object. The method then extends this area to encompass a previously identified area from a prior image, ensuring continuity in object tracking. This extension step helps maintain accurate tracking by accounting for movements or deformations of the object between frames. The method may also involve adjusting the area based on motion vectors or other predictive techniques to improve tracking robustness. The technique is particularly useful in applications such as surveillance, autonomous navigation, and video analysis, where reliable object detection and tracking are critical. By dynamically adjusting the area of interest, the method reduces errors caused by partial occlusions or rapid movements, enhancing the overall accuracy of object tracking in sequential images.
11. The method according to claim 9 , wherein: in the step (e), at least a portion of the second touch points are distributed in the extended part of the at least one area.
This invention relates to touch-sensitive input systems, specifically improving touch detection in extended or irregularly shaped touch-sensitive areas. The problem addressed is the difficulty in accurately detecting touch points in areas that extend beyond a standard touch-sensitive surface, such as edges or curved surfaces, where conventional touch detection methods may fail or produce unreliable results. The method involves detecting touch points on a touch-sensitive surface, where the surface includes at least one area that extends beyond a primary touch-sensitive region. The method first identifies a set of first touch points within the primary region. Then, it determines a second set of touch points in the extended part of the area, which may include regions where touch detection is less reliable. The method ensures that at least some of the second touch points are distributed within the extended part, improving coverage and accuracy in these areas. This distribution may involve interpolating or extrapolating touch data from the primary region to enhance detection in the extended part. The method may also adjust touch sensitivity or processing parameters to account for variations in the extended area, ensuring consistent performance across the entire touch-sensitive surface. The result is a more robust touch detection system that works effectively in both standard and extended touch-sensitive regions.
12. The method according to claim 9 , further includes steps following the termination of the iteration: determining a third calibration data for the touchscreen using the kinematic parameters and using the second position values; and computationally correcting errors of position measurement of the touchscreen for the rest areas using the third calibration data.
This invention relates to touchscreen calibration, specifically addressing errors in position measurement across different areas of a touchscreen. The problem arises when touchscreens exhibit inconsistent accuracy, particularly in regions not actively used during calibration, leading to measurement errors. The solution involves a multi-step calibration process that improves positional accuracy across the entire touchscreen surface. The method begins by collecting first position values from a touchscreen during an initial calibration phase, where a user or automated system interacts with specific calibration points. Kinematic parameters, such as velocity and acceleration, are then derived from these interactions. A second calibration phase follows, where additional position values are gathered, and a second calibration dataset is generated using these values and the kinematic parameters. This step refines the calibration model to account for dynamic touch behaviors. After the iterative calibration process concludes, a third calibration dataset is computed using the kinematic parameters and the second position values. This final dataset is applied to correct positional measurement errors in areas of the touchscreen not previously calibrated, ensuring uniform accuracy across the entire surface. The method leverages dynamic touch data to enhance calibration precision, particularly in regions where traditional static calibration methods may fail. This approach improves touchscreen responsiveness and reliability in applications requiring high positional accuracy.
13. The method according to claim 1 , wherein: in the step (e), the at least area is extended to enclose the previous one.
This invention relates to a method for extending a defined area in a system, likely for purposes such as boundary adjustment, spatial analysis, or object tracking. The method addresses the problem of dynamically adjusting an area to include previously defined regions, ensuring continuity or expansion of coverage without gaps. The process involves multiple steps, including defining an initial area, analyzing spatial relationships, and iteratively expanding the area to encompass prior regions. The key innovation is the step where the current area is extended to fully enclose the previous area, ensuring seamless integration. This may be applied in fields like computer vision, geographic information systems, or automated mapping, where maintaining consistent spatial boundaries is critical. The method ensures that new areas are not isolated but rather build upon existing ones, improving accuracy and coherence in spatial data processing. The solution is particularly useful in scenarios requiring real-time updates or where historical data must be preserved within expanded boundaries.
14. The method according to claim 13 , wherein: in the step (e), at least a portion of the second touch points are distributed in the extended part of the at least one area.
A method for touch input processing in electronic devices addresses the challenge of accurately detecting and interpreting touch interactions, particularly in areas with extended or irregular touch-sensitive regions. The method involves capturing touch data from a touch-sensitive surface, identifying initial touch points, and determining a touch area based on these points. The method then extends this touch area beyond the initial points to account for potential touch variations or inaccuracies. In a subsequent step, additional touch points are detected, and at least some of these points are distributed within the extended area. This distribution helps improve touch recognition by ensuring that touch inputs are accurately mapped to the intended touch-sensitive regions, even if the initial touch points are slightly offset. The method may also involve adjusting the extended area based on the detected touch points to refine the touch detection process. This approach enhances touch sensitivity and reduces errors in touch-based interfaces, particularly in devices with complex or non-standard touch-sensitive surfaces.
15. The method according to claim 13 , further includes steps following the termination of the iteration: determining a third calibration data for the touchscreen using the kinematic parameters and using the second position values; and computationally correcting errors of position measurement of the touchscreen for the rest areas using the third calibration data.
This invention relates to touchscreen calibration, specifically addressing errors in position measurement across different regions of a touchscreen. The problem solved is the inconsistency in touch accuracy between frequently used areas (active areas) and less frequently used areas (rest areas) of a touchscreen. Over time, active areas may experience wear or drift, while rest areas may lack sufficient calibration data, leading to measurement errors. The method involves iteratively calibrating the touchscreen by applying a first calibration data to the active areas and a second calibration data to the rest areas. After calibration iterations, kinematic parameters (e.g., touch movement patterns) are analyzed to refine calibration. A third calibration data is then generated using these parameters and the second position values from the rest areas. This third calibration data is applied to computationally correct position measurement errors in the rest areas, ensuring uniform accuracy across the entire touchscreen surface. The approach dynamically adjusts calibration based on usage patterns, improving long-term reliability and precision.
16. The method according to claim 1 , wherein: in the step (e), at least a portion of the second touch points are distributed in the extended part of the at least one area.
A method for touch input processing in electronic devices addresses the challenge of accurately detecting and interpreting touch inputs, particularly in areas with extended or irregular touch-sensitive regions. The method involves capturing touch data from a touch-sensitive surface, identifying touch points from the captured data, and determining the positions of these touch points relative to predefined areas on the surface. The method then classifies the touch points into primary and secondary groups based on their positions and characteristics. In a subsequent step, at least some of the secondary touch points are distributed within an extended part of at least one predefined area, ensuring that the touch input is accurately mapped to the intended region. This distribution step helps improve touch accuracy and responsiveness, especially in devices with complex or non-standard touch-sensitive layouts, such as those with curved edges or multiple interactive zones. The method may also involve filtering or adjusting the touch points to reduce noise and enhance precision. By dynamically distributing secondary touch points within extended areas, the method ensures that touch inputs are correctly interpreted, even in challenging touch surface configurations.
17. The method according to claim 1 , further includes steps following the termination of the iteration: determining a third calibration data for the touchscreen using the kinematic parameters and using the second position values; and computationally correcting errors of position measurement of the touchscreen for the rest areas using the third calibration data.
This invention relates to touchscreen calibration, specifically addressing errors in position measurement across the touchscreen surface. The method involves iteratively adjusting calibration data to improve accuracy, particularly in areas not directly touched during calibration. The process begins by collecting first position values from touch events on the touchscreen, then determining first calibration data based on these values. A kinematic model is applied to estimate second position values for areas not directly touched, using the first calibration data and kinematic parameters. These second position values are then used to refine the calibration, generating second calibration data. After the iteration terminates, a third calibration data set is computed using the kinematic parameters and the second position values. This third calibration data is applied to correct position measurement errors in the remaining areas of the touchscreen, ensuring uniform accuracy across the entire surface. The method leverages kinematic modeling to enhance calibration in untouched regions, improving overall touchscreen performance.
18. A system for calibrating a touchscreen panel including an industrial robot, comprising: the touchscreen panel being configured to: (a) define at least one area of the touchscreen with predetermined accuracy for position measuring; (b) record a plurality of kinematic parameters of the industrial robot on a plurality of first touch points on the at least one area of the touchscreen; (c) record a plurality of first position values on the plurality of first touch points on the at least one area of the touchscreen; (d) determine a first calibration data for the kinematic model of the industrial robot using the kinematic parameters and using the first position values; (e) computationally correct errors of the kinematic model of the industrial robot using the first calibration data; (f) record a plurality of second position values on a plurality of second touch points on the at least one area with at least a portion of its border extending outwards; (g) determine a second calibration data for the touchscreen using the kinematic parameters and using the second position values; (h) computationally correct errors of position measurement of the touchscreen using the second calibration data; and iteratively repeat the steps (b) through (h) for different postures of the industrial robot until the iteration step no longer results in significant improvement of the error correction of the kinematic model of the industrial robot.
The system calibrates a touchscreen panel using an industrial robot to improve accuracy in position measurement. The touchscreen defines a calibration area with precise positional accuracy. The robot touches multiple points within this area, recording its kinematic parameters (e.g., joint angles, positions) and the corresponding touchscreen position values. These data are used to generate calibration data for the robot's kinematic model, correcting errors in its movement. The process then extends to the touchscreen's border, recording additional position values to calibrate the touchscreen itself, correcting any measurement inaccuracies. The system iteratively repeats this process with different robot postures until further iterations no longer significantly improve calibration accuracy. This ensures both the robot's movement and the touchscreen's position sensing are optimized for high-precision applications, such as industrial automation or robot-assisted human-machine interfaces. The iterative approach refines calibration by progressively reducing errors in both the robot's kinematic model and the touchscreen's positional data.
19. An industrial robot arranged in a working range of a touchscreen panel, comprising: a robot controller and a robot memory being configured to execute instructions to: (a) define at least one area of the touchscreen with predetermined accuracy for position measuring; (b) record a plurality of kinematic parameters of the industrial robot on a plurality of first touch points on the at least one area of the touchscreen; (c) record a plurality of first position values on the plurality of first touch points on the at least one area of the touchscreen; (d) determine a first calibration data for the kinematic model of the industrial robot using the kinematic parameters and using the first position values; (e) computationally correct errors of the kinematic model of the industrial robot using the first calibration data; (f) record a plurality of second position values on a plurality of second touch points on the at least one area with at least a portion of its border extending outwards; (g) determine a second calibration data for the touchscreen using the kinematic parameters and using the second position values; (h) computationally correct errors of position measurement of the touchscreen using the second calibration data; and iteratively repeat the steps (b) through (h) for different postures of the industrial robot until the iteration step no longer results in significant improvement of the error correction of the kinematic model of the industrial robot.
This invention relates to an industrial robot system designed to calibrate both the robot's kinematic model and a touchscreen panel's position measurement accuracy. The system addresses inaccuracies in robot positioning and touchscreen coordinate mapping, which can lead to misalignment in applications requiring precise interaction between the robot and the touchscreen. The industrial robot is positioned within the working range of a touchscreen panel. A robot controller and memory execute instructions to perform a multi-step calibration process. First, the system defines a specific area on the touchscreen with high positional accuracy for measurement. The robot then records kinematic parameters (e.g., joint angles, end-effector positions) and corresponding position values at multiple touch points within this area. Using this data, the system generates calibration data to correct errors in the robot's kinematic model. Next, the robot records additional position values at touch points near the defined area's border, extending outward. This data is used to generate calibration data for the touchscreen, correcting its position measurement errors. The process iterates, adjusting the robot's posture and repeating the steps until further iterations no longer significantly improve calibration accuracy. This iterative approach ensures both the robot's movement and the touchscreen's coordinate system are accurately aligned, enhancing precision in applications like automated touchscreen testing or interaction.
20. A touchscreen panel, including a touchscreen panel controller and touchscreen panel memory being configured to execute instructions to: (a) define at least one area of the touchscreen with predetermined accuracy for position measuring; (b) record a plurality of kinematic parameters of the industrial robot on a plurality of first touch points on the at least one area of the touchscreen; (c) record a plurality of first position values on the plurality of first touch points on the at least one area of the touchscreen; (d) determine a first calibration data for the kinematic model of the industrial robot using the kinematic parameters and using the first position values; (e) computationally correct errors of the kinematic model of the industrial robot using the first calibration data; (f) record a plurality of second position values on a plurality of second touch points on the at least one area with at least a portion of its border extending outwards; (g) determine a second calibration data for the touchscreen using the kinematic parameters and using the second position values; (h) computationally correct errors of position measurement of the touchscreen using the second calibration data; and iteratively repeat the steps (b) through (h) for different postures of the industrial robot until the iteration step no longer results in significant improvement of the error correction of the kinematic model of the industrial robot.
This invention relates to a touchscreen panel system for calibrating an industrial robot's kinematic model and improving touchscreen position accuracy. The system addresses inaccuracies in robot positioning and touchscreen measurements, which can lead to misalignment in automated tasks. The touchscreen panel includes a controller and memory that execute instructions to define a specific area of the touchscreen with precise position measurement accuracy. The system records kinematic parameters of the industrial robot at multiple touch points within this area, along with corresponding position values. Using these data, it generates first calibration data to correct errors in the robot's kinematic model. The system then records additional position values at second touch points, including those extending beyond the defined area, to generate second calibration data for correcting touchscreen measurement errors. The process iteratively repeats for different robot postures until further iterations no longer significantly improve error correction. This iterative approach ensures both the robot's kinematic model and the touchscreen's position accuracy are refined, enhancing overall system precision in industrial applications.
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March 31, 2020
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